Buildings are an integral part of our everyday lives. The process of planning, designing and constructing these buildings has evolved over several thousands of years. Today, especially for modern facilities that are places from which to deliver complex services (like healthcare facilities), the steps followed to physically realize such buildings are very complicated and require a high degree of skilled labor that spans several different disciplines.
This complexity poses a huge challenge in terms of time, money and other resources expended in order to build a viable facility that can be used to deliver the intended services in an efficient and profitable way. Several industries and services have met similar complexity challenges by changing their work flow and adapting it to better exploit fast growing and inexpensive computational resources. This has resulted in an increased productivity in those industries.
However, the emergence of technological and computational capabilities has found limited adoption in the well established processes of building design and construction. As a result, there has been little gain in overall productivity, which is desperately needed today to meet the growing demand in complexity. For example, it has been found that while all other non-farming industries have doubled their productivity from 1964 to 2004, the building industry brethren have actually fallen behind.
While a plethora of reasons exist as to why construction productivity has not kept up with other areas, it is possible that conventional methods used in the building design and construction industry are not amenable to applying technology in general and computational technology in particular. Almost all other industries have gained in productivity due to the smart adaptation of computing technology, but, for reasons not immediately apparent, the construction industry has not seen any similar gains.
Buildings come in all different shapes and sizes and the complexity of buildings varies depending on their use. For example, from many different perspectives, a healthcare building such as a hospital is much more complex than an empty warehouse building. The complexity of a building becomes apparent when one tries to mathematically describe, model, simulate, optimize, and verify a building design such as the design of a hospital. In particular, the mathematical description, modeling, simulation, optimization, and verification are each a complex combination of three dimensional (3D) space and temporal operations. Characteristics of the 3D space include, for example, specifics of the building shell and core, the size and layout and function of the rooms, and routing of the building infrastructure. Characteristics of the temporal operations include, for example, the services provided within the building, load on the building (e.g., volume of patients), and dynamic environmental conditions (e.g., internal/external temperature, light, energy cost, etc).
Additionally, a fundamental challenge in complex building design is one of pattern matching. In particular, a fundamental challenge in designing a successful building is to match the expected temporal operations (e.g. human movement/workflow patterns) to the possible three-dimensional spaces (e.g., the physical space patterns). That is, the task of building design is a task of pattern matching in which patterns of function are matched to patterns of form.
In a healthcare facility, there are many complex functions (functional patterns) being performed simultaneously. For example, such functions include administration, admitting, diagnostic, imaging, acute care, observation, rehabilitation, surgery, laboratory, emergency, pharmacy, neonatal, delivery, information technology, sanitation, facilities, cafeteria, kitchen, etc. Each of the functions involves temporal operations that are performed within a particular physical three-dimensional space (spatial pattern) within the healthcare facility. In conventional building design processes, the three-dimensional spaces that are used to support the functions are selected by humans in a manual process from design templates that have been developed over time and have proven to be effective in supporting a particular function.
Because healthcare facilities can provide many complex functions (functional patterns), with each functional pattern utilizing a unique three-dimensional space (space pattern), the task of pattern matching can quickly become a very complex matching problem. Traditional manual building design techniques typically evaluate only a very small number of the total possible pattern matches.